How do Computerized Models Link to Other Policy Formulation Tools?
Computer models are normally combined with other policy formulation tools to make them (more) effective in decision making processes (cf. Ewert et al. 2009). For example, scientists use participatory methods (see Chapter 2, this volume) to translate policy problems and views into researchable questions, scenarios and indicators. This is crucial for engagement and contextualization of the modelling work and something that has been ignored too often in past modelling studies. Scenarios are employed to benchmark a policy change against a baseline situation in which policies do not change, or to explore explicit assumptions on drivers of change that are not part of the model (exogenous as opposed to endogenous variables which are part of the model) (see Chapter 3, this volume; Therond et al. 2009). Scientists also use indicators (see Chapter 4, this volume) to characterize different dimensions, aspects and criteria of sustainability; computer models allow for their quantitative assessment (Alkan Olsson et al. 2009). Aggregated or summary indicators can also be used to aggregate and present complex outcomes of computer models. For that purpose various kinds of visualization tools can also be employed, ranging from GIS, spider webs and various kinds of diagrams.
Cost-benefit analysis (see Chapter 7, this volume) can also be part of computer models (Janssen and van Ittersum 2007; Britz et al. 2012), though an important distinction is that the models as covered in this chapter try to present objectives and indicators in their own physical units rather than expressing everything in monetary terms. To weigh different criteria or objectives, for instance economic versus environmental, multi-criteria assessment methods (see Chapter 6, this volume) may be used ex post (Paracchini et al. 2011), after the model has been used; the objectives or indicators quantified by the model can be weighed using MCA techniques to reveal trade-offs between objectives and to identify optimal compromises. Although this step may be appealing for stakeholders or decision makers to arrive at 'single best options or solutions', the danger of weighing is that differences in opinion and relevance are rendered implicit. In the end, this may hinder transparent discussions and decisions.